Quality assessment and interference detection in targeted mass spectrometry data using machine learning.

Advances in the field of targeted proteomics and mass spectrometry have significantly improved assay sensitivity and multiplexing capacity. The high-throughput nature of targeted proteomics experiments has increased the rate of data production, which requires development of novel analytical tools to keep up with data processing demand. Currently, development and validation of targeted mass spectrometry assays require manual inspection of chromatographic peaks from large datasets to ensure quality, a process that is time consuming, prone to inter- and intra-operator variability and limits the efficiency of data interpretation from targeted proteomics analyses. To address this challenge, we have developed TargetedMSQC, an R package that facilitates quality control and verification of chromatographic peaks from targeted proteomics datasets. This tool calculates metrics to quantify several quality aspects of a chromatographic peak, e.g. symmetry, jaggedness and modality, co-elution and shape similarity of monitored transitions in a peak group, as well as the consistency of transitions' ratios between endogenous analytes and isotopically labeled internal standards and consistency of retention time across multiple runs. The algorithm takes advantage of supervised machine learning to identify peaks with interference or poor chromatography based on a set of peaks that have been annotated by an expert analyst. Using TargetedMSQC to analyze targeted proteomics data reduces the time spent on manual inspection of peaks and improves both speed and accuracy of interference detection. Additionally, by allowing the analysts to customize the tool for application on different datasets, TargetedMSQC gives the users the flexibility to define the acceptable quality for specific datasets. Furthermore, automated and quantitative assessment of peak quality offers a more objective and systematic framework for high throughput analysis of targeted mass spectrometry assay datasets and is a step towards more robust and faster assay implementation.

Alterations in Lysosomal, Glial and Neurodegenerative Biomarkers in Patients with Sporadic and Genetic Forms of Frontotemporal Dementia.

Background: Frontotemporal dementia (FTD) is the most common cause of early-onset dementia with 10-20% of cases caused by mutations in one of three genes: GRN, C9orf72, or MAPT. To effectively develop therapeutics for FTD, the identification and characterization of biomarkers to understand disease pathogenesis and evaluate the impact of specific therapeutic strategies on the target biology as well as the underlying disease pathology are essential. Moreover, tracking the longitudinal changes of these biomarkers throughout disease progression is crucial to discern their correlation with clinical manifestations for potential prognostic usage. Methods: We conducted a comprehensive investigation of biomarkers indicative of lysosomal biology, glial cell activation, synaptic and neuronal health in cerebrospinal fluid (CSF) and plasma from non-carrier controls, sporadic FTD (symptomatic non-carriers) and symptomatic carriers of mutations in GRN, C9orf72, or MAPT, as well as asymptomatic GRN mutation carriers. We also assessed the longitudinal changes of biomarkers in GRN mutation carriers. Furthermore, we examined biomarker levels in disease impacted brain regions including middle temporal gyrus (MTG) and superior frontal gyrus (SFG) and disease-unaffected inferior occipital gyrus (IOG) from sporadic FTD and symptomatic GRN carriers. Results: We confirmed glucosylsphingosine (GlcSph), a lysosomal biomarker regulated by progranulin, was elevated in the plasma from GRN mutation carriers, both symptomatic and asymptomatic. GlcSph and other lysosomal biomarkers such as ganglioside GM2 and globoside GB3 were increased in the disease affected SFG and MTG regions from sporadic FTD and symptomatic GRN mutation carriers, but not in the IOG, compared to the same brain regions from controls. The glial biomarkers GFAP in plasma and YKL40 in CSF were elevated in asymptomatic GRN carriers, and all symptomatic groups, except the symptomatic C9orf72 mutation group. YKL40 was also increased in SFG and MTG regions from sporadic FTD and symptomatic GRN mutation carriers. Neuronal injury and degeneration biomarkers NfL in CSF and plasma, and UCHL1 in CSF were elevated in patients with all forms of FTD. Synaptic biomarkers NPTXR, NPTX1/2, and VGF were reduced in CSF from patients with all forms of FTD, with the most pronounced reductions observed in symptomatic MAPT mutation carriers. Furthermore, we demonstrated plasma NfL was significantly positively correlated with disease severity as measured by CDR+NACC FTLD SB in genetic forms of FTD and CSF NPTXR was significantly negatively correlated with CDR+NACC FTLD SB in symptomatic GRN and MAPT mutation carriers. Conclusions: In conclusion, our comprehensive investigation replicated alterations in biofluid biomarkers indicative of lysosomal function, glial activation, synaptic and neuronal health across sporadic and genetic forms of FTD and unveiled novel insights into the dysregulation of these biomarkers within brain tissues from patients with GRN mutations. The observed correlations between biomarkers and disease severity open promising avenues for prognostic applications and for indicators of drug efficacy in clinical trials. Our data also implicated a complicated relationship between biofluid and tissue biomarker changes and future investigations should delve into the mechanistic underpinnings of these biomarkers, which will serve as a foundation for the development of targeted therapeutics for FTD.

Discovery and Preclinical Pharmacology of NX-2127, an Orally Bioavailable Degrader of Bruton's Tyrosine Kinase with Immunomodulatory Activity for the Treatment of Patients with B Cell Malignancies.

Bruton's tyrosine kinase (BTK), a member of the TEC family of kinases, is an essential effector of B-cell receptor (BCR) signaling. Chronic activation of BTK-mediated BCR signaling is a hallmark of many hematological malignancies, which makes it an attractive therapeutic target. Pharmacological inhibition of BTK enzymatic function is now a well-proven strategy for the treatment of patients with these malignancies. We report the discovery and characterization of NX-2127, a BTK degrader with concomitant immunomodulatory activity. By design, NX-2127 mediates the degradation of transcription factors IKZF1 and IKZF3 through molecular glue interactions with the cereblon E3 ubiquitin ligase complex. NX-2127 degrades common BTK resistance mutants, including BTKC481S. NX-2127 is orally bioavailable, exhibits in vivo degradation across species, and demonstrates efficacy in preclinical oncology models. NX-2127 has advanced into first-in-human clinical trials and achieves deep and sustained degradation of BTK following daily oral dosing at 100 mg.

Kinase-impaired BTK mutations are susceptible to clinical-stage BTK and IKZF1/3 degrader NX-2127.

Increasing use of covalent and noncovalent inhibitors of Bruton's tyrosine kinase (BTK) has elucidated a series of acquired drug-resistant BTK mutations in patients with B cell malignancies. Here we identify inhibitor resistance mutations in BTK with distinct enzymatic activities, including some that impair BTK enzymatic activity while imparting novel protein-protein interactions that sustain B cell receptor (BCR) signaling. Furthermore, we describe a clinical-stage BTK and IKZF1/3 degrader, NX-2127, that can bind and proteasomally degrade each mutant BTK proteoform, resulting in potent blockade of BCR signaling. Treatment of chronic lymphocytic leukemia with NX-2127 achieves >80% degradation of BTK in patients and demonstrates proof-of-concept therapeutic benefit. These data reveal an oncogenic scaffold function of mutant BTK that confers resistance across clinically approved BTK inhibitors but is overcome by BTK degradation in patients.

Maximizing the sensitivity and reliability of peptide identification in large-scale proteomic experiments by harnessing multiple search engines.

Despite recent advances in qualitative proteomics, the automatic identification of peptides with optimal sensitivity and accuracy remains a difficult goal. To address this deficiency, a novel algorithm, Multiple Search Engines, Normalization and Consensus is described. The method employs six search engines and a re-scoring engine to search MS/MS spectra against protein and decoy sequences. After the peptide hits from each engine are normalized to error rates estimated from the decoy hits, peptide assignments are then deduced using a minimum consensus model. These assignments are produced in a series of progressively relaxed false-discovery rates, thus enabling a comprehensive interpretation of the data set. Additionally, the estimated false-discovery rate was found to have good concordance with the observed false-positive rate calculated from known identities. Benchmarking against standard proteins data sets (ISBv1, sPRG2006) and their published analysis, demonstrated that the Multiple Search Engines, Normalization and Consensus algorithm consistently achieved significantly higher sensitivity in peptide identifications, which led to increased or more robust protein identifications in all data sets compared with prior methods. The sensitivity and the false-positive rate of peptide identification exhibit an inverse-proportional and linear relationship with the number of participating search engines.

Calpain-mediated tau fragmentation is altered in Alzheimer's disease progression.

The aggregation of intracellular tau protein is a major hallmark of Alzheimer's disease (AD). The extent and the stereotypical spread of tau pathology in the AD brain are correlated with cognitive decline during disease progression. Here we present an in-depth analysis of endogenous tau fragmentation in a well-characterized cohort of AD and age-matched control subjects. Using protein mass spectrometry and Edman degradation to interrogate endogenous tau fragments in the human brain, we identified two novel proteolytic sites, G323 and G326, as major tau cleavage events in both normal and AD cortex. These sites are located within the sequence recently identified as the structural core of tau protofilaments, suggesting an inhibitory mechanism of fibril formation. In contrast, a different set of novel cleavages showed a distinct increase in late stage AD. These disease-associated sites are located outside of the protofilament core sequence. We demonstrate that calpain 1 specifically cleaves at both the normal and diseased sites in vitro, and the site selection is conformation-dependent. Monomeric tau is predominantly cleaved at G323/G326 (normal sites), whereas oligomerization increases cleavages at the late-AD-associated sites. The fragmentation patterns specific to disease and healthy states suggest novel regulatory mechanisms of tau aggregation in the human brain.

Cancer biomarker discovery via low molecular weight serum proteome profiling - Where is the tumor?

Time-course analyses of rapidly processed serum performed in parallel by SELDI and nanoscale LC-MS/MS have revealed the temporal correlation of several literature-based disease markers with ex vivo driven events such that their in vivo existence in healthy subjects is questionable. Identification by MS/MS reveals these putative biomarkers to be byproducts of the coagulation cascade and platelet activation and suggests plasmatic analysis may be preferred. In a pilot plasmatic study, a cohort of naïve prostate cancer (PCa) samples were uniformly distinguished from their age-matched controls (n = 20) on the basis of multiple peptidic components; most notably by a derivative of complement C(4) at 1863 m/z (GLEEELQFSLGSKINVK, C4(1353-1369) ). The fully tryptic nature of this and other putative PCa discriminants is consistent with the cleavage specificity of common blood proteases and questions the need for tumor-derived proteolytic activities as has been proposed. In light of the known correlation of disregulated hemostasis with malignant disease, we suggest the underlying differentiating phenomena in these types of analyses may lie in the temporal disparity of sample activation such that the case (patient) samples are preactivated while the control samples are not.